engleski

Social Network Graph Analysis Using Machine Learning Techniques

This thesis provides a brief introduction to the field of social network analysis as well as network science in general. A special focus was given to embedding algorithms and their application in standard network analysis techniques. A Python application has been implemented and documented for the purpose of evaluating the graph embedding techniques node2vec and DeepWalk on machine learning tasks such as node classification and link prediction as well as community detection (node clustering). The evaluation was undertaken on publicly available social network graphs and can be reproduced on other datasets to determine the best algorithm implementations and parameters on a case-to-case basis.

social network graph analysis ; network science ; graph embedding algorithms ; node2vec ; DeepWalk ; machine learning ; node classification ; link prediction ; clustering ; community detection

nije evidentirano